INFO: underlay of /etc/localtime required more than 50 (88) bind mounts INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts 2023-07-14 17:05:50.395531: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 17:05:52.785484: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2023-07-14 17:05:52.789048: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1 2023-07-14 17:05:53.586799: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: pciBusID: 0000:0a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0 coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s 2023-07-14 17:05:53.586874: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 17:05:53.610595: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11 2023-07-14 17:05:53.610649: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11 2023-07-14 17:05:53.620014: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10 2023-07-14 17:05:53.624555: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10 2023-07-14 17:05:53.640223: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10 2023-07-14 17:05:53.644434: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11 2023-07-14 17:05:53.645356: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8 2023-07-14 17:05:53.677371: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0 2023-07-14 17:05:53.677817: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2023-07-14 17:05:53.679265: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 2023-07-14 17:05:53.700714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: pciBusID: 0000:0a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0 coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s 2023-07-14 17:05:53.700787: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 17:05:53.700823: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11 2023-07-14 17:05:53.700850: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11 2023-07-14 17:05:53.700874: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10 2023-07-14 17:05:53.700897: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10 2023-07-14 17:05:53.700919: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10 2023-07-14 17:05:53.700941: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11 2023-07-14 17:05:53.700963: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8 2023-07-14 17:05:53.743193: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0 2023-07-14 17:05:53.745548: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 17:05:55.720902: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix: 2023-07-14 17:05:55.721076: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0 2023-07-14 17:05:55.721090: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N 2023-07-14 17:05:55.727790: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:0a:00.0, compute capability: 8.0) 2023-07-14 17:05:57.881254: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them. /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors. , UserWarning)